Optimization of a goal maintenance task for use in clinical applications

Association of neurotransmitter pathway polygenic risk with specific symptom profiles in psychosis

A primary goal of psychiatry is to better understand the pathways that link genetic risk to psychiatric symptoms. Here, we tested association of diagnosis and endophenotypes with overall and neurotransmitter pathway-specific polygenic risk in patients with early-stage psychosis. Subjects included 205 demographically diverse cases with a psychotic disorder who underwent comprehensive psychiatric and neurological phenotyping and 115 matched controls. Following genotyping, we calculated polygenic scores (PGSs) for schizophrenia (SZ) and bipolar disorder (BP) using Psychiatric Genomics Consortium GWAS summary statistics. To test if overall genetic risk can be partitioned into affected neurotransmitter pathways, we calculated pathway PGSs (pPGSs) for SZ risk affecting each of four major neurotransmitter systems: glutamate, GABA, dopamine, and serotonin. Psychosis subjects had elevated SZ PGS versus controls; cases with SZ or BP diagnoses had stronger SZ or BP risk, respectively. There was no significant association within psychosis cases between individual symptom measures and overall PGS. However, neurotransmitter-specific pPGSs were moderately associated with specific endophenotypes; notably, glutamate was associated with SZ diagnosis and with deficits in cognitive control during task-based fMRI, while dopamine was associated with global functioning. Finally, unbiased endophenotype-driven clustering identified three diagnostically mixed case groups that separated on primary deficits of positive symptoms, negative symptoms, global functioning, and cognitive control. All clusters showed strong genome-wide risk. Cluster 2, characterized by deficits in cognitive control and negative symptoms, additionally showed specific risk concentrated in glutamatergic and GABAergic pathways. Due to the intensive characterization of our subjects, the present study was limited to a relatively small cohort. As such, results should be followed up with additional research at the population and mechanism level. Our study suggests pathway-based PGS analysis may be a powerful path forward to study genetic mechanisms driving psychiatric endophenotypes.

Cognitive Control in Schizophrenia: Advances in Computational Approaches

Psychiatric research is undergoing significant advances in an emerging subspeciality of computational psychiatry, building upon cognitive neuroscience research by expanding to neurocomputational modeling. Here, we illustrate some research trends in this domain using work on proactive cognitive control deficits in schizophrenia as an example. We provide a selective review of formal modeling approaches to understanding cognitive control deficits in psychopathology, focusing primarily on biologically plausible connectionist-level models as well as mathematical models that generate parameter estimates of putatively dissociable psychological or neural processes. We illustrate some of the advantages of these models in terms of understanding both cognitive control deficits in schizophrenia and the potential roles of effort and motivation. Further, we highlight critical future directions for this work, including a focus on establishing psychometric properties, additional work modeling psychotic symptoms and their interaction with cognitive control, and the need to expand both behavioral and neural modeling to samples that include individuals with different mental health conditions, allowing for the examination of dissociable neural or psychological substrates for seemingly similar cognitive impairments across disorders.

Association of neurotransmitter pathway polygenic risk with specific symptom profiles in psychosis

A primary goal of psychiatry is to better understand the pathways that link genetic risk to psychiatric symptoms. Here, we tested association of diagnosis and endophenotypes with overall and neurotransmitter pathway-specific polygenic risk in patients with early-stage psychosis. Subjects included 206 demographically diverse cases with a psychotic disorder who underwent comprehensive psychiatric and neurological phenotyping and 115 matched controls. Following genotyping, we calculated polygenic scores (PGSs) for schizophrenia (SZ) and bipolar disorder (BP) using Psychiatric Genomics Consortium GWAS summary statistics. To test if overall genetic risk can be partitioned into affected neurotransmitter pathways, we calculated pathway PGSs (pPGSs) for SZ risk affecting each of four major neurotransmitter systems: glutamate, GABA, dopamine, and serotonin. Psychosis subjects had elevated SZ PGS versus controls; cases with SZ or BP diagnoses had stronger SZ or BP risk, respectively. There was no significant association within psychosis cases between individual symptom measures and overall PGS. However, neurotransmitter-specific pPGSs were moderately associated with specific endophenotypes; notably, glutamate was associated with SZ diagnosis and with deficits in cognitive control during task-based fMRI, while dopamine was associated with global functioning. Finally, unbiased endophenotype-driven clustering identified three diagnostically mixed case groups that separated on primary deficits of positive symptoms, negative symptoms, global functioning, and cognitive control. All clusters showed strong genome-wide risk. Cluster 2, characterized by deficits in cognitive control and negative symptoms, additionally showed specific risk concentrated in glutamatergic and GABAergic pathways. Due to the intensive characterization of our subjects, the present study was limited to a relatively small cohort. As such, results should be followed up with additional research at the population and mechanism level. Our study suggests pathway-based PGS analysis may be a powerful path forward to study genetic mechanisms driving psychiatric endophenotypes.

Antiviral treatment in schizophrenia: a randomized pilot PET study on the effects of valaciclovir on neuroinflammation

BACKGROUND

Patients with schizophrenia experience cognitive impairment, which could be related to neuroinflammation in the hippocampus. The cause for such hippocampal inflammation is still unknown, but it has been suggested that herpes virus infection is involved. This study therefore aimed to determine whether add-on treatment of schizophrenic patients with the anti- viral drug valaciclovir would reduce hippocampal neuroinflammation and consequently improve cognitive symptoms.

METHODS

We performed a double-blind monocenter study in 24 male and female patients with schizophrenia, experiencing active psychotic symptoms. Patients were orally treated with the anti-viral drug valaciclovir for seven consecutive days (8 g/day). Neuroinflammation was measured with Positron Emission Tomography using the translocator protein ligand [11C]-PK11195, pre-treatment and at seven days post-treatment, as were psychotic symptoms and cognition.

RESULTS

Valaciclovir treatment resulted in reduced TSPO binding (39%) in the hippocampus, as well as in the brainstem, frontal lobe, temporal lobe, parahippocampal gyrus, amygdala, parietal lobe, occipital lobe, insula and cingulate gyri, nucleus accumbens and thalamus (31-40%) when using binding potential (BPND) as an outcome. With total distribution volume (VT) as outcome we found essentially the same results, but associations only approached statistical significance (p = 0.050 for hippocampus). Placebo treatment did not affect neuroinflammation. No effects of valaciclovir on psychotic symptoms or cognitive functioning were found.

CONCLUSION

We found a decreased TSPO binding following antiviral treatment, which could suggest a viral underpinning of neuroinflammation in psychotic patients. Whether this reduced neuroinflammation by treatment with valaciclovir has clinical implications and is specific for schizophrenia warrants further research.

Altered Associations Between Task Performance and Dorsolateral Prefrontal Cortex Activation During Cognitive Control in Schizophrenia

BACKGROUND

Dysfunctional cognitive control processes are now well understood to be core features of schizophrenia (SZ). A body of work suggests that the dorsolateral prefrontal cortex (DLPFC) plays a critical role in explaining cognitive control disruptions in SZ. Here, we examined relationships between DLPFC activation and drift rate (DR), a model-based performance measure that combines reaction time and accuracy, in people with SZ and healthy control (HC) participants.

METHODS

One hundred fifty-one people with recent-onset SZ spectrum disorders and 118 HC participants performed the AX-Continuous Performance Task during functional magnetic resonance imaging scanning. Proactive cognitive control-associated activation was extracted from left and right DLPFC regions of interest. Individual behavior was fit using a drift diffusion model, allowing DR to vary between task conditions.

RESULTS

Behaviorally, people with SZ showed significantly lower DRs than HC participants, particularly during high proactive control trial types ("B" trials). Recapitulating previous findings, the SZ group also demonstrated reduced cognitive control-associated DLPFC activation compared with HC participants. Furthermore, significant group differences were also observed in the relationship between left and right DLPFC activation with DR, such that positive relationships between DR and activation were found in HC participants but not in people with SZ.

CONCLUSIONS

These results suggest that DLPFC activation is less associated with cognitive control-related behavioral performance enhancements in SZ. Potential mechanisms and implications are discussed.

Dissociation of Cognitive Effort-Based Decision Making and Its Associations With Symptoms, Cognition, and Everyday Life Function Across Schizophrenia, Bipolar Disorder, and Depression

BACKGROUND

Anhedonia and amotivation are symptoms of many different mental health disorders that are frequently associated with functional disability, but it is not clear whether the same processes contribute to motivational impairments across disorders. This study focused on one possible factor, the willingness to exert cognitive effort, referred to as cognitive effort-cost decision making.

METHODS

We examined performance on the deck choice task as a measure of cognitive effort-cost decision making, in which people choose to complete an easy task for a small monetary reward or a harder task for larger rewards, in 5 groups: healthy control (n = 80), schizophrenia/schizoaffective disorder (n = 50), bipolar disorder with psychosis (n = 58), current major depression (n = 60), and past major depression (n = 51). We examined cognitive effort-cost decision making in relation to clinician and self-reported motivation symptoms, working memory and cognitive control performance, and life function measured by ecological momentary assessment and passive sensing.

RESULTS

We found a significant diagnostic group × reward interaction (F8,588 = 4.37, p < .001, ηp2 = 0.056). Compared with the healthy control group, the schizophrenia/schizoaffective and bipolar disorder groups, but not the current or past major depressive disorder groups, showed a reduced willingness to exert effort at the higher reward values. In the schizophrenia/schizoaffective and bipolar disorder groups, but not the major depressive disorder groups, reduced willingness to exert cognitive effort for higher rewards was associated with greater clinician-rated motivation impairments, worse working memory and cognitive control performance, and less engagement in goal-directed activities measured by ecological momentary assessment.

CONCLUSIONS

These findings suggest that the mechanisms contributing to motivational impairments differ among individuals with psychosis spectrum disorders versus depression.

Individual differences in computational psychiatry: a review of current challenges

Bringing precision to the understanding and treatment of mental disorders requires instruments for studying clinically relevant individual differences. One promising approach is the development of computational assays: integrating computational models with cognitive tasks to infer latent patient-specific disease processes in brain computations. While recent years have seen many methodological advancements in computational modelling and many cross-sectional patient studies, much less attention has been paid to basic psychometric properties (reliability and construct validity) of the computational measures provided by the assays. In this review, we assess the extent of this issue by examining emerging empirical evidence. We find that many computational measures suffer from poor psychometric properties, which poses a risk of invalidating previous findings and undermining ongoing research efforts using computational assays to study individual (and even group) differences. We provide recommendations for how to address these problems and, crucially, embed them within a broader perspective on key developments that are needed for translating computational assays to clinical practice.

Comparing the functional neuroanatomy of proactive and reactive control between patients with schizophrenia and healthy controls

Cognitive control deficits are associated with impaired executive functioning in schizophrenia. The Dual Mechanisms of Control framework suggests that proactive control requires sustained dorsolateral prefrontal activity, whereas reactive control marshals a larger network. However, primate studies suggest these processes are maintained by dual-encoding regions. To distinguish between these theories, we compared the distinctiveness of proactive and reactive control functional neuroanatomy. In a reanalysis of data from a previous study, 47 adults with schizophrenia and 56 controls completed the Dot Pattern Expectancy task during an fMRI scan examining proactive and reactive control in frontoparietal and medial temporal regions. Areas suggesting specialized control or between-group differences were tested for association with symptoms and task performance. Elastic net models additionally explored these areas' predictive abilities regarding performance. Most regions were active in both reactive and proactive control. However, evidence of specialized proactive control was found in the left middle and superior frontal gyri. Control participants showed greater proactive control in the left middle and right inferior frontal gyri. Elastic net models moderately predicted task performance and implicated various frontal gyri regions in control participants, with additional involvement of anterior cingulate and posterior parietal regions for reactive control. Elastic nets for patient participants implicated the inferior and superior frontal gyri, and posterior parietal lobe. Specialized cognitive control was unassociated with either performance or schizophrenia symptomatology. Future work is needed to clarify the distinctiveness of proactive and reactive control, and its role in executive deficits in severe psychopathology.

Planning on Autopilot? Associative Contributions to Proactive Control

Proactive cognitive control is thought to rely on the active maintenance of goals or contextual information in working memory. It is often measured using the AX-CPT, in which antecedent cues (A/B) are used to proactively prepare a response to a subsequently-presented probe (X/Y). Although control in this task purportedly requires active maintenance of information in working memory, it also provides conditions in which learning the contingencies between relevant events could influence performance via associative learning. We tested this hypothesis using a dot-pattern expectancy version of the AX-CPT whereby a set of new rules (test phase) for responding changed the control operations required for some previously trained cues, while keeping the operations the same for others, allowing us to measure associative interference. We also tested the relationship between associative interference and working memory capacity (operation span; Experiments 1-3) and tested the effect of applying working memory load during the initial acquisition period (Experiment 2) and during the test phase (Experiment 3). We found robust evidence of interference after the rule change based on previously learnt contingencies, suggesting that learnt contingencies come to influence proactive planning, even when they are task-irrelevant. This associative effect had no relationship with working memory capacity or load, based on a load manipulation commonly used in executive control tasks. The findings suggest that proactive control does not always require active maintenance of current goals and environmental cues in working memory. Instead, proactive control may run on autopilot if the individual can rely upon stable relationships in the environment to trigger planning and preparation. SIGNIFICANCE: Navigating daily life requires us to anticipate future events and plan our thoughts and actions accordingly to achieve our goals. This forward planning, or proactive control, is thought to be a resource-intensive and metabolically costly process that recruits higher-order cognitive functions, such as working memory, where relevant thoughts and actions have to be maintained online. The current study challenged this notion by finding that proactive control can be incrementally relegated to simpler processes based on one's learning of stable relationships in the environment, thereby reducing the need to actively maintain information online. Individuals can come to rely on underlying contingencies in stimuli associated with proactive control, even when it is detrimental to their goals.

Using Nonhuman Primate Models to Reverse-Engineer Prefrontal Circuit Failure Underlying Cognitive Deficits in Schizophrenia

In this chapter, I review studies in nonhuman primates that emulate the circuit failure in prefrontal cortex responsible for working memory and cognitive control deficits in schizophrenia. These studies have characterized how synaptic malfunction, typically induced by blockade of NMDAR, disrupts neural function and computation in prefrontal networks to explain errors in cognitive tasks that are seen in schizophrenia. This work is finding causal relationships between pathogenic events of relevance to schizophrenia at vastly different levels of scale, from synapses, to neurons, local, circuits, distributed networks, computation, and behavior. Pharmacological manipulation, the dominant approach in primate models, has limited construct validity for schizophrenia pathogenesis, as the disease results from a complex interplay between environmental, developmental, and genetic factors. Genetic manipulation replicating schizophrenia risk is more advanced in rodent models. Nonetheless, gene manipulation in nonhuman primates is rapidly advancing, and primate developmental models have been established. Integration of large scale neural recording, genetic manipulation, and computational modeling in nonhuman primates holds considerable potential to provide a crucial schizophrenia model moving forward. Data generated by this approach is likely to fill several crucial gaps in our understanding of the causal sequence leading to schizophrenia in humans. This causal chain presents a vexing problem largely because it requires understanding how events at very different levels of scale relate to one another, from genes to circuits to cognition to social interactions. Nonhuman primate models excel here. They optimally enable discovery of causal relationships across levels of scale in the brain that are relevant to cognitive deficits in schizophrenia. The mechanistic understanding of prefrontal circuit failure they promise to provide may point the way to more effective therapeutic interventions to restore function to prefrontal networks in the disease.

Cognitive [Computational] Neuroscience Test Reliability and Clinical Applications for Serious Mental Illness (CNTRaCS) Consortium: Progress and Future Directions

The development of treatments for impaired cognition in schizophrenia has been characterized as the most important challenge facing psychiatry at the beginning of the twenty-first century. The Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS) project was designed to build on the potential benefits of using tasks and tools from cognitive neuroscience to better understanding and treat cognitive impairments in psychosis. These benefits include: (1) the use of fine-grained tasks that measure discrete cognitive processes; (2) the ability to design tasks that distinguish between specific cognitive domain deficits and poor performance due to generalized deficits resulting from sedation, low motivation, poor test taking skills, etc.; and (3) the ability to link cognitive deficits to specific neural systems, using animal models, neuropsychology, and functional imaging. CNTRICS convened a series of meetings to identify paradigms from cognitive neuroscience that maximize these benefits and identified the steps need for translation into use in clinical populations. The Cognitive Neuroscience Test Reliability and Clinical Applications for Schizophrenia (CNTRaCS) Consortium was developed to help carry out these steps. CNTRaCS consists of investigators at five different sites across the country with diverse expertise relevant to a wide range of the cognitive systems identified as critical as part of CNTRICs. This work reports on the progress and current directions in the evaluation and optimization carried out by CNTRaCS of the tasks identified as part of the original CNTRICs process, as well as subsequent extensions into the Positive Valence systems domain of Research Domain Criteria (RDoC). We also describe the current focus of CNTRaCS, which involves taking a computational psychiatry approach to measuring cognitive and motivational function across the spectrum of psychosis. Specifically, the current iteration of CNTRaCS is using computational modeling to isolate parameters reflecting potentially more specific cognitive and visual processes that may provide greater interpretability in understanding shared and distinct impairments across psychiatric disorders.

TMS reveals distinct patterns of proactive and reactive inhibition in motor system activity

Response inhibition is our ability to suppress or cancel actions when required. Deficits in response inhibition are linked with a range of psychopathological disorders including addiction and OCD. Studies on response inhibition have largely focused on reactive inhibition-stopping an action when explicitly cued. Less work has examined proactive inhibition-preparation to stop ahead of time. In the current experiment, we studied both reactive and proactive inhibition by adopting a two-step continuous performance task (e.g., "AX"-CPT) often used to study cognitive control. By combining a dot pattern expectancy (DPX) version of this task with transcranial magnetic stimulation (TMS), we mapped changes in reactive and proactive inhibition within the motor system. Measured using motor-evoked potentials, we found modulation of corticospinal excitability at critical timepoints during the DPX when participants were preparing in advance to inhibit a response (at step 1: during the cue) and while inhibiting a response (at step 2: during the probe). Notably, motor system activity during early timepoints was predicted by a behavioural index of proactive capacity and could predict whether participants would later successfully inhibit their response. Our findings demonstrate that combining TMS with a two-step CPT such as the DPX can be useful for studying reactive and proactive inhibition, and reveal that successful inhibition is determined earlier than previously thought.

Domain-general conflict monitoring predicts neural and behavioral indices of linguistic error processing during reading comprehension

The ability to detect and respond to linguistic errors is critical for successful reading comprehension, but these skills can vary considerably across readers. In the current study, healthy adults (age 18-35) read short discourse scenarios for comprehension while monitoring for the presence of semantic anomalies. Using a factor analytic approach, we examined if performance in nonlinguistic conflict monitoring tasks (Stroop, AX-CPT) would predict individual differences in neural and behavioral measures of linguistic error processing. Consistent with this hypothesis, domain-general conflict monitoring predicted both readers' end-of-trial acceptability judgments and the amplitude of a late neural response (the P600) evoked by linguistic anomalies. The influence on the P600 was nonlinear, suggesting that online neural responses to linguistic errors are influenced by both the effectiveness and efficiency of domain-general conflict monitoring. These relationships were also highly specific and remained after controlling for variability in working memory capacity and verbal knowledge. Finally, we found that domain-general conflict monitoring also predicted individual variability in measures of reading comprehension, and that this relationship was partially mediated by behavioral measures of linguistic error detection. These findings inform our understanding of the role of domain-general executive functions in reading comprehension, with potential implications for the diagnosis and treatment of language impairments. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Transdisciplinary Preliminary Evaluation of Goal Maintenance in Cancer-Related Cognitive Impairment

Women treated for breast cancer often experience decreases in executive functioning, including goal maintenance, which interferes with daily living. The objective of this study was to conduct a preliminary comparison of cognitive neuroscience assessment performance with neuropsychological, self-report, and performance-based assessments of goal maintenance in women with breast cancer. Women treated for breast cancer in the preceding 3 years completed a battery of cognitive assessments. Relationships between assessment methods were evaluated using Spearman rho correlations. Consistent with prior literature, the AY condition of the Dot Pattern Expectancy (DPX) assessment had the highest error rate. No consistent relationships between the DPX and other methods of assessment were identified; however, some moderate correlations were identified between assessments. Women treated for breast cancer present with DPX performance patterns similar to that of healthy controls in past literature. A larger study is required to confirm relationships between measures of goal maintenance across disciplines.

Both unmedicated and medicated individuals with schizophrenia show impairments across a wide array of cognitive and reinforcement learning tasks

BACKGROUND

Schizophrenia is a disorder characterized by pervasive deficits in cognitive functioning. However, few well-powered studies have examined the degree to which cognitive performance is impaired even among individuals with schizophrenia not currently on antipsychotic medications using a wide range of cognitive and reinforcement learning measures derived from cognitive neuroscience. Such research is particularly needed in the domain of reinforcement learning, given the central role of dopamine in reinforcement learning, and the potential impact of antipsychotic medications on dopamine function.

METHODS

The present study sought to fill this gap by examining healthy controls (N = 75), unmedicated (N = 48) and medicated (N = 148) individuals with schizophrenia. Participants were recruited across five sites as part of the CNTRaCS Consortium to complete tasks assessing processing speed, cognitive control, working memory, verbal learning, relational encoding and retrieval, visual integration and reinforcement learning.

RESULTS

Individuals with schizophrenia who were not taking antipsychotic medications, as well as those taking antipsychotic medications, showed pervasive deficits across cognitive domains including reinforcement learning, processing speed, cognitive control, working memory, verbal learning and relational encoding and retrieval. Further, we found that chlorpromazine equivalency rates were significantly related to processing speed and working memory, while there were no significant relationships between anticholinergic load and performance on other tasks.

CONCLUSIONS

These findings add to a body of literature suggesting that cognitive deficits are an enduring aspect of schizophrenia, present in those off antipsychotic medications as well as those taking antipsychotic medications.

Data augmentation with Mixup: Enhancing performance of a functional neuroimaging-based prognostic deep learning classifier in recent onset psychosis

Although deep learning holds great promise as a prognostic tool in psychiatry, a limitation of the method is that it requires large training sample sizes to achieve replicable accuracy. This is problematic for fMRI datasets as they are typically small due to the considerable time, cost, and resources necessary to obtain them. A recently developed self-supervised learning method called Mixup may help overcome this challenge. In Mixup, the learner combines pairs of training instances to produce a virtual third instance that is a linear combination of the two instances and their labels. This procedure is also well-suited to the coregistered images typically found in fMRI datasets. Here we compared performance of a task fMRI-based deep learner with Mixup vs without Mixup on predicting response to treatment in recent onset psychosis. Whole brain fMRI time series data were extracted from a cognitive control task in 82 patients with recent onset psychosis and used to predict "Improver" (n = 47) vs "Non-Improver" (n = 35) status, with Improver defined as showing a 20 % reduction in total Brief Psychiatric Rating Scale score after 1 year of treatment. Mixup significantly improved performance (accuracy without Mixup: 76.5 % [95 % CI: 75.9-77.1 %]; accuracy with Mixup: 80.1 % [95 % CI: 79.4-80.8 %]). Ablation showed the improvement was due to improvement in both Improvers and Non-Improvers. These results suggest that using Mixup may significantly improve performance and reduce overfitting of fMRI-based prognostic deep learners and may also help overcome the small sample size challenge inherent to many neuroimaging datasets.

EXPRESS: Working Memory Capacity and Dual Mechanisms of Cognitive Control: An Experimental-Correlational Approach

Working memory is thought to be strongly related to cognitive control. Recent studies have sought to understand this relationship under the prism of the dual mechanisms of control (DMC) framework, in which cognitive control is thought to operate in two distinct modes: proactive and reactive. Several authors have concluded that a high working memory capacity is associated with a tendency to engage the more effective mechanism of proactive control. However, the predicted pattern of proactive control use has never been observed; correlational evidence is made difficult to interpret by the overall superiority of participants with a high working memory capacity: they tend to perform better even when proactive control should be detrimental. In two experiments, we used an experimental-correlational approach to experimentally induce the use of reactive or proactive control in the AX-CPT. The relation between working memory capacity and performance was unaffected, incompatible with the hypothesis that the better performance of participants with a high working memory capacity in the task is due to their use of proactive control. It remains unclear how individual differences in working memory capacity relate to cognitive control under the DMC framework.

The impact of pandemic-related worry on cognitive functioning and risk-taking

Here, we sought to quantify the effects of experienced fear and worry, engendered by the COVID-19 pandemic, on both cognitive abilities-speed of information processing, task-set shifting, and proactive control-as well as economic risk-taking. Leveraging a repeated-measures cross-sectional design, we examined the performance of 1517 participants, collected during the early phase of the pandemic in the US (April-June 2020), finding that self-reported pandemic-related worry predicted deficits in information processing speed and maintenance of goal-related contextual information. In a classic economic risk-taking task, we observed that worried individuals' choices were more sensitive to the described outcome probabilities of risky actions. Overall, these results elucidate the cognitive consequences of a large-scale, unpredictable, and uncontrollable stressor, which may in turn play an important role in individuals' understanding of, and adherence to safety directives both in the current crisis and future public health emergencies.

Neurocognitive subprocesses of working memory performance

Working memory (WM) has been defined as the active maintenance and flexible updating of goal-relevant information in a form that has limited capacity and resists interference. Complex measures of WM recruit multiple subprocesses, making it difficult to isolate specific contributions of putatively independent subsystems. The present study was designed to determine whether neurophysiological indicators of proposed subprocesses of WM predict WM performance. We recruited 200 individuals defined by care-seeking status and measured neural responses using electroencephalography (EEG), while participants performed four WM tasks. We extracted spectral and time-domain EEG features from each task to quantify each of the hypothesized WM subprocesses: maintenance (storage of content), goal maintenance, and updating. We then used EEG measures of each subprocess as predictors of task performance to evaluate their contribution to WM. Significant predictors of WM capacity included contralateral delay activity and frontal theta, features typically associated with maintenance (storage of content) processes. In contrast, significant predictors of reaction time and its variability included contingent negative variation and the P3b, features typically associated with goal maintenance and updating. Broadly, these results suggest two principal dimensions that contribute to WM performance, tonic processes during maintenance contributing to capacity, and phasic processes during stimulus processing that contribute to response speed and variability. The analyses additionally highlight that reliability of features across tasks was greater (and comparable to that of WM performance) for features associated with stimulus processing (P3b and alpha), than with maintenance (gamma, theta and cross-frequency coupling).

Dynamic reorganization of the frontal parietal network during cognitive control and episodic memory

Higher cognitive functioning is supported by adaptive reconfiguration of large-scale functional brain networks. Cognitive control (CC), which plays a vital role in flexibly guiding cognition and behavior in accordance with our goals, supports a range of executive functions via distributed brain networks. These networks process information dynamically and can be represented as functional connectivity changes between network elements. Using graph theory, we explored context-dependent network reorganization in 56 healthy adults performing fMRI tasks from two cognitive domains that varied in CC and episodic-memory demands. We examined whole-brain modular structure during the DPX task, which engages proactive CC in the frontal-parietal cognitive-control network (FPN), and the RiSE task, which manipulates CC demands at encoding and retrieval during episodic-memory processing, and engages FPN, the medial-temporal lobe and other memory-related networks in a context dependent manner. Analyses revealed different levels of network integration and segregation. Modularity analyses revealed greater brain-wide integration across tasks in high CC conditions compared to low CC conditions. Greater network reorganization occurred in the RiSE memory task, which is thought to require coordination across multiple brain networks, than in the DPX cognitive-control task. Finally, FPN, ventral attention, and visual systems showed within network connectivity effects of cognitive control; however, these cognitive systems displayed varying levels of network reorganization. These findings provide insight into how brain networks reorganize to support differing task contexts, suggesting that the FPN flexibly segregates during focused proactive control and integrates to support control in other domains such as episodic memory.

Global disruption in excitation-inhibition balance can cause localized network dysfunction and Schizophrenia-like context-integration deficits

Poor context integration, the process of incorporating both previous and current information in decision making, is a cognitive symptom of schizophrenia. The maintenance of the contextual information has been shown to be sensitive to changes in excitation-inhibition (EI) balance. Many regions of the brain are sensitive to EI imbalances, however, so it is unknown how systemic manipulations affect the specific regions that are important to context integration. We constructed a multi-structure, biophysically-realistic agent that could perform context-integration as is assessed by the dot pattern expectancy task. The agent included a perceptual network, a memory network, and a decision making system and was capable of successfully performing the dot pattern expectancy task. Systemic manipulation of the agent’s EI balance produced localized dysfunction of the memory structure, which resulted in schizophrenia-like deficits at context integration. When the agent’s pyramidal cells were less excitatory, the agent fixated upon the cue and initiated responding later than the default agent, which were like the deficits one would predict that individuals on the autistic spectrum would make. This modelling suggests that it may be possible to parse between different types of context integration deficits by adding distractors to context integration tasks and by closely examining a participant’s reaction times.

Schizophrenia is a debilitating mental health disorder and its underlying etiology is currently unknown. Neural imbalances in the neural excitation and inhibition of specific regions of the brain have been hypothesized to cause symptoms of schizophrenia. Most regions of the brain have specific excitation-inhibition balances that permit their functioning in the processing of information. How systemic changes in the excitation-inhibition balance cause specific deficits and dysfunction within neural circuits is unknown. A common cognitive deficit in schizophrenia is difficulty with context integration, which is the ability to successfully use previous and current information when making decisions. We assessed how this symptom could be caused by an imbalance in neural excitation and inhibition by simulating the effects of potential imbalances in a model agent. Global imbalances in the agent’s neural excitation and inhibition led to impairment of specific circuits. These dysfunctional circuits produced behavioral deficits that were like those observed in individuals with schizophrenia. These simulations suggested how specific neural circuits may be disrupted by global changes in excitation or inhibition, ways to improve the assessment of context integration, new approaches to analyzing behavior, and why it may be beneficial to assess context integration in autism spectrum disorder.

Comparing machine and deep learning-based algorithms for prediction of clinical improvement in psychosis with functional magnetic resonance imaging

Previous work using logistic regression suggests that cognitive control-related frontoparietal activation in early psychosis can predict symptomatic improvement after 1 year of coordinated specialty care with 66% accuracy. Here, we evaluated the ability of six machine learning (ML) algorithms and deep learning (DL) to predict "Improver" status (>20% improvement on Brief Psychiatric Rating Scale [BPRS] total score at 1-year follow-up vs. baseline) and continuous change in BPRS score using the same functional magnetic resonance imaging-based features (frontoparietal activations during the AX-continuous performance task) in the same sample (individuals with either schizophrenia (n = 65, 49M/16F, mean age 20.8 years) or Type I bipolar disorder (n = 17, 9M/8F, mean age 21.6 years)). 138 healthy controls were included as a reference group. "Shallow" ML methods included Naive Bayes, support vector machine, K Star, AdaBoost, J48 decision tree, and random forest. DL included an explainable artificial intelligence (XAI) procedure for understanding results. The best overall performances (70% accuracy for the binary outcome and root mean square error = 9.47 for the continuous outcome) were achieved using DL. XAI revealed left DLPFC activation was the strongest feature used to make binary classification decisions, with a classification activation threshold (adjusted beta = .017) intermediate to the healthy control mean (adjusted beta = .15, 95% CI = -0.02 to 0.31) and patient mean (adjusted beta = -.13, 95% CI = -0.37 to 0.11). Our results suggest DL is more powerful than shallow ML methods for predicting symptomatic improvement. The left DLPFC may be a functional target for future biomarker development as its activation was particularly important for predicting improvement.

Deep brain stimulation for psychiatric disorders: From focal brain targets to cognitive networks

Deep brain stimulation (DBS) is a promising intervention for treatment-resistant psychiatric disorders, particularly major depressive disorder (MDD) and obsessive-compulsive disorder (OCD). Up to 90% of patients who have not recovered with therapy or medication have reported benefit from DBS in open-label studies. Response rates in randomized controlled trials (RCTs), however, have been much lower. This has been argued to arise from surgical variability between sites, and recent psychiatric DBS research has focused on refining targeting through personalized imaging. Much less attention has been given to the fact that psychiatric disorders arise from dysfunction in distributed brain networks, and that DBS likely acts by altering communication within those networks. This is in part because psychiatric DBS research relies on subjective rating scales that make it difficult to identify network biomarkers. Here, we overview recent DBS RCT results in OCD and MDD, as well as the follow-on imaging studies. We present evidence for a new approach to studying DBS' mechanisms of action, focused on measuring objective cognitive/emotional deficits that underpin these and many other mental disorders. Further, we suggest that a focus on cognition could lead to reliable network biomarkers at an electrophysiologic level, especially those related to inter-regional synchrony of the local field potential (LFP). Developing the network neuroscience of DBS has the potential to finally unlock the potential of this highly specific therapy.

Differing functional mechanisms underlie cognitive control deficits in psychotic spectrum disorders

BACKGROUND

Functional underpinnings of cognitive control deficits in unbiased samples (i.e., all comers) of patients with psychotic spectrum disorders (PSD) remain actively debated. While many studies suggest hypofrontality in the lateral prefrontal cortex (PFC) and greater deficits during proactive relative to reactive control, few have examined the full hemodynamic response.

METHODS

Patients with PSD (n = 154) and healthy controls (n = 65) performed the AX continuous performance task (AX-CPT) during rapid (460 ms) functional neuroimaging and underwent full clinical characterization.

RESULTS

Behavioural results indicated generalized cognitive deficits (slower and less accurate) across proactive and reactive control conditions in patients with PSD relative to healthy controls. We observed a delayed/prolonged neural response in the left dorsolateral PFC, the sensorimotor cortex and the superior parietal lobe during proactive control for patients with PSD. These proactive hemodynamic abnormalities were better explained by negative rather than by positive symptoms or by traditional diagnoses according to the Diagnostic and Statistical Manual of Mental Disorders Fourth Edition, Text Revision (DSM-IV-TR), with subsequent simulations unequivocally demonstrating how these abnormalities could be erroneously interpreted as hypoactivation. Conversely, true hypoactivity, unassociated with clinical symptoms or DSM-IV-TR diagnoses, was observed within the ventrolateral PFC during reactive control.

LIMITATIONS

In spite of guidance for AX-CPT use in neuroimaging studies, one-third of patients with PSD could not perform the task above chance and were more clinically impaired.

CONCLUSION

Current findings question the utility of the AX-CPT for neuroimaging-based appraisal of cognitive control across the full spectrum of patients with PSD. Previously reported lateral PFC "hypoactivity" during proactive control may be more indicative of a delayed/prolonged neural response, important for rehabilitative purposes. Negative symptoms may better explain certain behavioural and hemodynamic abnormalities in patients with PSD relative to DSM-IV-TR diagnoses.

Predicting psychosis risk using a specific measure of cognitive control: a 12-month longitudinal study

BACKGROUND

Identifying risk factors of individuals in a clinical-high-risk state for psychosis are vital to prevention and early intervention efforts. Among prodromal abnormalities, cognitive functioning has shown intermediate levels of impairment in CHR relative to first-episode psychosis and healthy controls, highlighting a potential role as a risk factor for transition to psychosis and other negative clinical outcomes. The current study used the AX-CPT, a brief 15-min computerized task, to determine whether cognitive control impairments in CHR at baseline could predict clinical status at 12-month follow-up.

METHODS

Baseline AX-CPT data were obtained from 117 CHR individuals participating in two studies, the Early Detection, Intervention, and Prevention of Psychosis Program (EDIPPP) and the Understanding Early Psychosis Programs (EP) and used to predict clinical status at 12-month follow-up. At 12 months, 19 individuals converted to a first episode of psychosis (CHR-C), 52 remitted (CHR-R), and 46 had persistent sub-threshold symptoms (CHR-P). Binary logistic regression and multinomial logistic regression were used to test prediction models.

RESULTS

Baseline AX-CPT performance (d-prime context) was less impaired in CHR-R compared to CHR-P and CHR-C patient groups. AX-CPT predictive validity was robust (0.723) for discriminating converters v. non-converters, and even greater (0.771) when predicting CHR three subgroups.

CONCLUSIONS

These longitudinal outcome data indicate that cognitive control deficits as measured by AX-CPT d-prime context are a strong predictor of clinical outcome in CHR individuals. The AX-CPT is brief, easily implemented and cost-effective measure that may be valuable for large-scale prediction efforts.

Using prefrontal transcranial direct current stimulation (tDCS) to enhance proactive cognitive control in schizophrenia

The goal of this study was to use transcranial direct current stimulation (tDCS) to examine the role of the prefrontal cortex (PFC) in neural oscillatory activity associated with proactive cognitive control in schizophrenia. To do so, we tested the impact of PFC-targeted tDCS on behavioral and electrophysiological markers of proactive cognitive control engagement in individuals with schizophrenia. Using a within-participants, double-blinded, sham-controlled crossover design, we recorded EEG while participants with schizophrenia completed a proactive cognitive control task (the Dot Pattern Expectancy (DPX) Task), after receiving 20 min of active prefrontal stimulation at 2 mA or sham stimulation. We hypothesized that active stimulation would enhance proactive cognitive control, leading to changes in behavioral performance on the DPX task and in activity in the gamma frequency band during key periods of the task designed to tax proactive cognitive control. The results showed significant changes in the pattern of error rates and increases in EEG gamma power as a function of tDCS condition (active or sham), that were indicative of enhanced proactive cognitive control. These findings, considered alongside our previous work in healthy adults, provides novel support for the role gamma oscillations in proactive cognitive control and they suggest that frontal tDCS may be a promising approach to enhance proactive cognitive control in schizophrenia.

Cognitive Impairment and Diminished Neural Responses Constitute a Biomarker Signature of Negative Symptoms in Psychosis

The treatment of negative symptoms (NS) in psychosis represents an urgent unmet medical need given the significant functional impairment it contributes to psychosis syndromes. The lack of progress in treating NS is impacted by the lack of known pathophysiology or associated quantitative biomarkers, which could provide tools for research. This current analysis investigated potential associations between NS and an extensive battery of behavioral and brain-based biomarkers in 932 psychosis probands from the B-SNIP database. The current analyses examined associations between PANSS-defined NS and (1) cognition, (2) pro-/anti-saccades, (3) evoked and resting-state electroencephalography (EEG), (4) resting-state fMRI, and (5) tractography. Canonical correlation analyses yielded symptom-biomarker constructs separately for each biomarker modality. Biomarker modalities were integrated using canonical discriminant analysis to summarize the symptom-biomarker relationships into a "biomarker signature" for NS. Finally, distinct biomarker profiles for 2 NS domains ("diminished expression" vs "avolition/apathy") were computed using step-wise linear regression. NS were associated with cognitive impairment, diminished EEG response amplitudes, deviant resting-state activity, and oculomotor abnormalities. While a connection between NS and poor cognition has been established, association to neurophysiology is novel, suggesting directions for future mechanistic studies. Each biomarker modality was related to NS in distinct and complex ways, giving NS a rich, interconnected fingerprint and suggesting that any one biomarker modality may not adequately capture the full spectrum of symptomology.

Differential Roles of Mediodorsal Nucleus of the Thalamus and Prefrontal Cortex in Decision-Making and State Representation in a Cognitive Control Task Measuring Deficits in Schizophrenia

The mediodorsal nucleus of the thalamus (MD) is reciprocally connected with the prefrontal cortex (PFC), and although the MD has been implicated in a range of PFC-dependent cognitive functions (Watanabe and Funahashi, 2012; Mitchell and Chakraborty, 2013; Parnaudeau et al., 2018), little is known about how MD neurons in the primate participate specifically in cognitive control, a capability that reflects the ability to use contextual information (such as a rule) to modify responses to environmental stimuli. To learn how the MD-PFC thalamocortical network is engaged to mediate forms of cognitive control that are selectively disrupted in schizophrenia, we trained male monkeys to perform a variant of the AX continuous performance task, which reliably measures cognitive control deficits in patients (Henderson et al., 2012) and used linear multielectrode arrays to record neural activity in the MD and PFC simultaneously. We found that the two structures made clearly different contributions to distributed processing for cognitive control: MD neurons were specialized for decision-making and response selection, whereas prefrontal neurons were specialized to preferentially encode the environmental state on which the decision was based. In addition, we observed that functional coupling between MD and PFC was strongest when the decision as to which of the two responses in the task to execute was being made. These findings delineate unique contributions of MD and PFC to distributed processing for cognitive control and characterized neural dynamics in this network associated with normative cognitive control performance.SIGNIFICANCE STATEMENT Cognitive control is fundamental to healthy human executive functioning (Miller and Cohen, 2001) and deficits in patients with schizophrenia relate to decreased functional activation of the MD thalamus and the prefrontal cortex (Minzenberg et al., 2009), which are reciprocally linked (Goldman-Rakic and Porrino, 1985; Xiao et al., 2009). We carry out simultaneous neural recordings in the MD and PFC while monkeys perform a cognitive control task translated from patients with schizophrenia to relate thalamocortical dynamics to cognitive control performance. Our data suggest that state representation and decision-making computations for cognitive control are preferentially performed by PFC and MD, respectively. This suggests experiments to parse decision-making and state representation deficits in patients while providing novel computational targets for future therapies.

Latent Profiles of Cognitive Control, Episodic Memory, and Visual Perception Across Psychiatric Disorders Reveal a Dimensional Structure

Although meta-analyses suggest that schizophrenia (SZ) is associated with a more severe neurocognitive phenotype than mood disorders such as bipolar disorder, considerable between-subject heterogeneity exists in the phenotypic presentation of these deficits across mental illnesses. Indeed, it is unclear whether the processes that underlie cognitive dysfunction in these disorders are unique to each disease or represent a common neurobiological process that varies in severity. Here we used latent profile analysis (LPA) across 3 distinct cognitive domains (cognitive control, episodic memory, and visual integration; using data from the CNTRACS consortium) to identify distinct profiles of patients across psychotic illnesses. LPA was performed on a sample of 223 psychosis patients (59 with Type I bipolar disorder, 88 with SZ, and 76 with schizoaffective disorder). Seventy-three healthy control participants were included for comparison but were not included in sample LPA. Three latent profiles ("Low," "Moderate," and "High" ability) were identified as the underlying covariance across the 3 domains. The 3-profile solution provided highly similar fit to a single continuous factor extracted by confirmatory factor analysis, supporting a unidimensional structure. Diagnostic ratios did not significantly differ between profiles, suggesting that these profiles cross diagnostic boundaries (an exception being the Low ability profile, which had only one bipolar patient). Profile membership predicted Brief Psychiatric Rating Scale and Young Mania Rating Scale symptom severity as well as everyday communication skills independent of diagnosis. Biological, clinical and methodological implications of these findings are discussed.

ERP evidence for the effect of working memory span training on working memory maintenance: A randomized controlled trial

There is a lot of debate in the literature with regards to whether the effects of working memory span training generalize to working memory tasks that are different from the trained task, however, there is little evidence to date supporting this idea. The present randomized controlled trial included 80 undergraduate students who were randomly assigned to either the experimental group (N = 40) or the control group (N = 40) in order to receive a working memory span intervention for 20 sessions over the course of 4 weeks. Brain electrophysiological signals during a dot pattern expectancy (DPX) task and a change detection task were recorded both before and after the intervention. The amplitudes of characteristic event-related potential (ERP) components reflecting working memory maintenance capability during the delay period of both tasks (i.e., the contingent negative variation or CNV, derived from the DPX task, and the contralateral delay activity or CDA, derived from the change detection task) were used as the primary outcome measures. Our data indicated that the intervention resulted in specific changes in both, the CNV and the CDA, suggesting that working memory span training generalized to working memory maintenance processes as observed in working memory tasks that were different from the trained task. We conclude that working memory span training might serve as a useful tool to improve working memory maintenance capability. Trial Registration: Chinese Clinical Trial Registry (chiCTR-INR-17011728).

The characteristics of cognitive neuroscience tests in a schizophrenia cognition clinical trial: Psychometric properties and correlations with standard measures

In comparison to batteries of standard neuropsychological tests, cognitive neuroscience tests may offer a more specific assessment of discrete neurobiological processes that may be aberrant in schizophrenia. However, more information regarding psychometric properties and correlations with standard neuropsychological tests and functional measures is warranted to establish their validity as treatment outcome measures. The N-back and AX-Continuous Performance Task (AX-CPT) are two promising cognitive neuroscience tests designed to measure specific components of working memory and contextual processing respectively. In the current study, we report the psychometric properties of multiple outcome measures from these two tests as well as their correlations with standard neuropsychological measures and functional capacity measures. The results suggest that while the AX-CPT and N-back display favorable psychometric properties, they do not exhibit greater sensitivity or specificity with functional measures than standard neurocognitive tests.

Baseline Frontoparietal Task-Related BOLD Activity as a Predictor of Improvement in Clinical Symptoms at 1-Year Follow-Up in Recent-Onset Psychosis

OBJECTIVE

The early course of illness in psychotic disorders is highly variable, and predictive biomarkers of treatment response have been lacking. Trial and error remains the basis for care in early psychosis, and poor outcomes are common. Early prediction of nonimprovement in response to treatment could help identify those who would benefit from alternative and/or supplemental interventions. The goal of this study was to evaluate the ability of functional MRI (fMRI) measures of cognitive control-related brain circuitry collected at baseline to predict symptomatic response in patients after 1 year.

METHODS

Patients with recent-onset (<2 years) psychotic disorders (N=82) in early psychosis specialty care were classified as improvers (>20% improvement in total score on the Brief Psychiatric Rating Scale [BPRS] at 1-year follow-up compared with baseline) or as nonimprovers. Behavioral (d' context) and fMRI (proactive control-associated activation in a priori frontoparietal regions of interest) measures of cognitive control were then evaluated on their ability to predict BPRS improvement using linear and logistic regression.

RESULTS

Cognitive control-associated measures significantly predicted BPRS improvement and improver status, with 70% positive predictive value, 60% negative predictive value, and 66% accuracy. Only the fMRI-based measure (and not the behavioral measure) significantly predicted status.

CONCLUSIONS

These results suggest that frontoparietal activation during cognitive control performance at baseline significantly predicts subsequent symptomatic improvement during early psychosis specialty care. Potential implications for fMRI-based personalized patient treatment are discussed.

Delay knowledge and trial set count modulate use of proactive versus reactive control: A meta-analytic review

The AX-continuous performance task (AX-CPT) and dot pattern expectancy (DPX) are the predominant cognitive paradigms used to assess the relative utilization of proactive versus reactive cognitive control. Experimental parameters vary widely between studies and systematically between different modalities (i.e., fMRI vs. EEG) with unknown consequences for the implementation of control. This meta-analytic review systematically surveyed these bodies of literature (k = 43, 73 data points) to resolve how cue-probe delay knowledge, delay length, and trial set count modulate the preferential use of proactive versus reactive control. In healthy young adults, delay knowledge and increasing trial set count each bias participants toward greater proactive control. Further, the interaction of delay knowledge and trial set count accounts for ~40% of variability in proactive/reactive control performance. As trial count varies reliably between experimental modalities, it is critical to understand how these parameters activate distinct cognitive processes and tap into different neural mechanisms for control. Subgroup analyses revealed important distinctions from our results in healthy young adults. Healthy, slightly older adults (ages 30-45 years) performed more reactively compared to healthy young adults. In addition, participants with schizophrenia showed evidence of more proactive control as trial set count increased. In light of this meta-analytic review, we conclude that delay knowledge and trial set length are important parameters to account for in the assessment of proactive versus reactive control. More broadly, this metaregression provides strong evidence that cognitive control becomes more reactive when timing demands are not known, and that both healthy persons and persons with schizophrenia shift toward proactive control with increasing repetitions of a task set.

Cross-diagnostic analysis of cognitive control in mental illness: Insights from the CNTRACS consortium

BACKGROUND

In recent years, psychiatry research has increasingly focused on understanding mental illnesses from a cross-diagnostic, dimensional perspective in order to better align their neurocognitive features with underlying neurobiological mechanisms. In this multi-site study, we examined two measures of cognitive control (d-prime context and lapsing rate) during the Dot Probe Expectancy (DPX) version of the AX-Continuous Performance Task in patients with either schizophrenia (SZ), schizoaffective disorder (SZ-A), or Type I bipolar disorder (BD) as well as healthy control (HC) subjects. We hypothesized significantly lower d-prime context and higher lapsing rate in SZ and SZ-A patients and intermediate levels in BD patients relative to HC.

METHODS

72 HC, 84 SZ, 77 SZ-A, and 58 BD patients (ages 18-56) were included in the final study sample.

RESULTS

Significant main effects of diagnosis were observed on d-prime context (F(3,279) = 9.59, p < 0.001) and lapsing (F(3,279) = 8.08, p < 0.001). A priori linear contrasts suggesting intermediate dysfunction in BD patients were significant (p < 0.001), although post-hoc tests showed the BD group was only significantly different from HC on d-prime context. Group results for d-prime context remained significant after covarying for lapsing rate. Primary behavioral measures were associated with mania and disorganization symptoms as well as everyday functioning.

CONCLUSIONS

These findings suggest a continuum of dysfunction in cognitive control (particularly d-prime context) across diagnostic categories in psychiatric illness. These results further suggest that lapsing and d-prime context, while related, make unique contributions towards explaining deficits in cognitive control in these disorders.

Perceptual timing in children with attention-deficit/hyperactivity disorder (ADHD) as measured by computer-based experiments versus real-life tasks: protocol for a cross-sectional experimental study in an ambulatory setting

INTRODUCTION

The goal of this study is to get a better understanding of the fundamentals of perceptual timing deficits, that is, difficulties with estimating durations of explicitly attended temporal intervals, in children with attention-deficit/hyperactivity disorder (ADHD). Whereas these deficits were repeatedly demonstrated in laboratory studies using computer-based timing tasks, we will additionally implement a more practical task reflecting real-life activity. In doing so, the research questions of the planned study follow a hierarchically structured path 'from lab to life': Are the timing abilities of children with ADHD really disturbed both in the range of milliseconds and in the range of seconds? What causes these deficits? Do children with ADHD rather display a global perceptual timing deficit, or do different 'timing types' exist? Are timing deficits present during real-life activities as well, and are they based on the same mechanisms as in computerised tasks?

METHODS AND ANALYSES

A quasi-experimental study with two groups of male children aged 8-12 years (ADHD; controls) and with a cross-sectional design will be used to address our research questions. Statistical analyses of the dependent variables will comprise (repeated) measures analyses of variance, stepwise multiple regression analyses and latent class models. With an estimated dropout rate of 25%, power analysis indicated a sample size of 140 subjects (70 ADHD, 70 controls) to detect medium effect sizes.

ETHICS AND DISSEMINATION

Ethics approval was obtained from the ethics committee of the Faculty of Medicine, University of Rostock. Results will be disseminated to researcher, clinician and patient communities in peer-reviewed journals and at scientific conferences, at a meeting of the local ADHD competence network and on our web page which will summarise the study results in an easily comprehensible manner.

TRIAL REGISTRATION NUMBER

DRKS00015760.

Immediate versus delayed control demands elicit distinct mechanisms for instantiating proactive control

Cognitive control is critical for dynamically guiding goal-directed behavior, particularly when applying preparatory, or proactive, control processes. However, it is unknown how proactive control is modulated by timing demands. This study investigated how timing demands may instantiate distinct neural processes and contribute to the use of different types of proactive control. In two experiments, healthy young adults performed the AX-Continuous Performance Task (AX-CPT) or Dot Pattern Expectancy (DPX) task. The delay between informative cue and test probe was manipulated by block to be short (1s) or long (~3s). We hypothesized that short cue-probe delays would rely more on a rapid goal updating process (akin to task-switching), whereas long cue-probe delays would utilize more of an active maintenance process (akin to working memory). Short delay lengths were associated with specific impairments in rare probe accuracy. EEG responses to control-demanding cues revealed delay-specific neural signatures, which replicated across studies. In the short delay condition, EEG activities associated with task-switching were specifically enhanced, including increased early anterior positivity ERP amplitude (accompanying greater mid-frontal theta power) and a larger late differential switch positivity. In the long delay condition, we observed study-specific sustained increases in ERP amplitude following control-demanding cues, which may be suggestive of active maintenance. Collectively, these findings suggest that timing demands may instantiate distinct proactive control processes. These findings suggest a reevaluation of AX-CPT and DPX as pure assessments of working memory and highlight the need to understand how presumably benign task parameters, such as cue-probe delay length, significantly alter cognitive control.

Prefrontal transcranial direct current stimulation (tDCS) enhances behavioral and EEG markers of proactive control

This study examined the effects of stimulation targeting dorsolateral prefrontal cortex (DLPFC) on behavioral and neural oscillatory markers of proactive cognitive control in healthy adults. We hypothesized that active stimulation targeting the DLPFC would enhance proactive control compared to sham, leading to changes in the pattern of error rates and gamma-band power on the Dot Pattern Expectancy (DPX) task. We recorded EEG while participants completed the DPX, after receiving either 20 minutes of active DLPFC stimulation at 2 mA or sham stimulation in a counterbalanced within-participants design. The results showed significant tDCS-induced changes in the pattern of error rates on the DPX task indicative of enhanced proactive control, as well as predicted increases in gamma power associated with the engagement of proactive control. These results provide support for the role of DLPFC-mediated gamma activity in proactive cognitive control, and further, indicate that proactive control can be enhanced with non-invasive neurostimulation.

Longitudinal stability of cognitive control in early psychosis: Nondegenerative deficits across diagnoses

Cognitive impairment, particularly in the domain of cognitive control, is characteristic of schizophrenia (SZ) spectrum and bipolar disorders (BDs). The longitudinal trajectory of these impairments, however, remains unclear. Indeed, some studies have observed degeneration and others stability or even improvement over time in these illnesses. Here we examined the longitudinal stability of the AX-Continuous Performance Task (AX-CPT), a cognitive control task, in 52 patients with recent-onset SZ (<2 years from first study measurement), 20 patients with recent-onset BD Type I with psychotic features, and 70 healthy control subjects. Subjects performed the AX-CPT at 2 time points separated by an average of 365 days (range 270-620). Previously identified deficits in cognitive control were replicated in both patient groups. No effects of time or interactions between time and diagnosis were observed. Intraclass correlation coefficients also suggested AX-CPT performance was stable across time for all diagnostic groups. Although performance was stable on average, a positive association was noted between change in cognitive control and change in disorganization symptom severity across patient groups. In conclusion, the present findings suggest that deficits in cognitive control are present in both disorders and stable over the early course of psychotic illness. No evidence was observed for progression or deterioration of cognitive control or differential recovery in SZ compared to BD. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The contribution of the contingent negative variation (CNV) to goal maintenance

The dot pattern expectancy (DPX) task has been strongly recommended as a measure of goal maintenance, which is impaired in schizophrenia patients. The current event-related potential (ERP) study was designed mainly to identify the ERP component that could represent the goal maintenance process of the DPX task as indexed by the error rate of the BX vs. AY (E_BX-AY). We focused our analysis on the cue-phased contingent negative variation (CNV) and found a significant association between the E_BX-AY and the amplitude of the difference wave of cue B vs. cue A (CNV_B-A) (for CP₃, β=-0.262, P=0.001; for CP_Z, β=-0.184, P=0.025; for CP₄, β=-0.201, P=0.015). Lower E_BX-AY (better goal maintenance) was correlated with larger CNV_B-A. Further analysis found a significant association between the error rate of AY condition (E_AY) and the amplitude of CNV_A (for CP₃, β=-0.180, P=0.029; for CP_Z, β=-0.184, P=0.024; for CP₄, β=-0.208, P=0.011) and a significant association between the error rate of BX condition (E_BX) and the amplitude of CNV_B-A (for CP₃, β=-0.198, P=0.016; for CP_Z, β=-0.165, P=0.043; for CP₄, β=-0.151, P=0.066), but not the amplitude of the CNV_B (all P>0.05). All these results together suggested that the cue-phased CNV could be used to represent the goal maintenance process. Future research needs to verify these results with schizophrenia patients.

Effort-cost decision-making in psychosis and depression: could a similar behavioral deficit arise from disparate psychological and neural mechanisms?

Motivational impairment is a common feature of both depression and psychosis; however, the psychological and neural mechanisms that give rise to motivational impairment in these disorders are poorly understood. Recent research has suggested that aberrant effort-cost decision-making (ECDM) may be a potential contributor to motivational impairment in both psychosis and depression. ECDM refers to choices that individuals make regarding the amount of 'work' they are willing to expend to obtain a certain outcome or reward. Recent experimental work has suggested that those with psychosis and depression may be less willing to expend effort to obtain rewards compared with controls, and that this effort deficit is related to motivational impairment in both disorders. In the current review, we aim to summarize the current literature on ECDM in psychosis and depression, providing evidence for transdiagnostic impairment. Next, we discuss evidence for the hypothesis that a seemingly similar behavioral ECDM deficit might arise from disparate psychological and neural mechanisms. Specifically, we argue that effort deficits in psychosis might be largely driven by deficits in cognitive control and the neural correlates of cognitive control processes, while effort deficits in depression might be largely driven by reduced reward responsivity and the associated neural correlates of reward responsivity. Finally, we will provide some discussion regarding future directions, as well as interpretative challenges to consider when examining ECDM transdiagnostically.

Multivariate Relationships Between Cognition and Brain Anatomy Across the Psychosis Spectrum

BACKGROUND

Cognitive and structural brain abnormalities range from mild to severe in psychosis. The relationships of specific cognitive functions to specific brain structures across the psychosis spectrum is less certain.

METHODS

Participants (n = 678) with bipolar, schizoaffective, or schizophrenia psychoses and healthy control subjects were recruited via the Bipolar-Schizophrenia Network for Intermediate Phenotypes. The Schizo-Bipolar Scale was used to create a psychosis continuum (from purely affective to purely nonaffective). Canonical correlation between 14 cognitive measures and structural brain measures (gray matter volume, cortical thickness, cortical surface area, and local gyrification indices) for 68 neocortical regions yielded constructs that defined shared cognition-brain structure relationships. Canonical discriminant analysis was used to integrate these constructs and efficiently summarize cognition-brain structure relationships across the psychosis continuum.

RESULTS

General cognition was associated with larger gray matter volumes and thicker cortices but smaller cortical surface area in frontoparietal regions. Working memory was associated with larger volume and surface area in frontotemporal regions. Faster response speed was associated with thicker frontal cortices. Constructs that captured general cognitive ability and working memory and their relationship to cortical volumes primarily defined an ordered psychosis spectrum (purely affective, least abnormal through purely nonaffective, and most abnormal). A construct that captured general cognitive ability and its relationship to cortical surface area differentiated purely affective cases from other groups.

CONCLUSIONS

General cognition and working memory with cortical volume deviations characterized more nonaffective psychoses. Alternatively, affective psychosis cases with general cognitive deficits had deviations in cortical surface area, perhaps accounting for heterogeneous findings across previous studies.

Levels of Cognitive Control: A Functional Magnetic Resonance Imaging-Based Test of an RDoC Domain Across Bipolar Disorder and Schizophrenia

In recent years, the boundaries of psychopathology as defined by diagnostic categories have been criticized as inadequately 'carving nature at its joints' with respect to the neurobiology of major mental disorders. In 2010 the NIMH launched the Research Domain Criteria (RDoC) framework for understanding mental illnesses as brain circuit disorders that extend beyond DSM-defined diagnoses. In the present study we focus on cognitive dysfunction, a core feature of schizophrenia (SZ) and bipolar disorder (BPD), and use functional magnetic resonance imaging (fMRI) during a cognitive control (CC) task in recent onset patients to test the hypothesis that at a behavioral and underlying neural circuitry level these deficits exist on a continuum (as opposed to showing categorical differences) across the two disorders. In total, 53 healthy controls, 24 recent (<1 y) onset patients with BPD Type I with psychotic features, and 70 recent onset patients with SZ performed the AX-Continuous Performance Task while undergoing event-related fMRI at 1.5 T. In addition to behavior task-associated response was examined in frontoparietal regions-of-interest. In an a priori contrast-based analysis, significant deficits across patient groups (vs controls) were observed on CC-associated performance as well as frontoparietal response. These analyses further revealed a continuum of deficits in which BPD showed intermediate levels of CC relative to controls and SZ. Poor CC was associated with poverty and disorganization symptoms across patient groups. These results support the hypothesis that CC dysfunction in BPD and SZ reflects a continuum of deficits that cuts across traditional, DSM-based classification. Implications for the neurobiology of these diseases are discussed.

The Role of Psychometrics in Individual Differences Research in Cognition: A Case Study of the AX-CPT

Investigating individual differences in cognition requires addressing questions not often thought about in standard experimental designs, especially regarding the psychometric properties of the task. Using the AX-CPT cognitive control task as a case study example, we address four concerns that one may encounter when researching the topic of individual differences in cognition. First, we demonstrate the importance of variability in task scores, which in turn directly impacts reliability, particularly when comparing correlations in different populations. Second, we demonstrate the importance of variability and reliability for evaluating potential failures to replicate predicted correlations, even within the same population. Third, we demonstrate how researchers can turn to evaluating psychometric properties as a way of evaluating the feasibility of utilizing the task in new settings (e.g., online administration). Lastly, we show how the examination of psychometric properties can help researchers make informed decisions when designing a study, such as determining the appropriate number of trials for a task.

Explicit and implicit reinforcement learning across the psychosis spectrum

Motivational and hedonic impairments are core features of a variety of types of psychopathology. An important aspect of motivational function is reinforcement learning (RL), including implicit (i.e., outside of conscious awareness) and explicit (i.e., including explicit representations about potential reward associations) learning, as well as both positive reinforcement (learning about actions that lead to reward) and punishment (learning to avoid actions that lead to loss). Here we present data from paradigms designed to assess both positive and negative components of both implicit and explicit RL, examine performance on each of these tasks among individuals with schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis, and examine their relative relationships to specific symptom domains transdiagnostically. None of the diagnostic groups differed significantly from controls on the implicit RL tasks in either bias toward a rewarded response or bias away from a punished response. However, on the explicit RL task, both the individuals with schizophrenia and schizoaffective disorder performed significantly worse than controls, but the individuals with bipolar did not. Worse performance on the explicit RL task, but not the implicit RL task, was related to worse motivation and pleasure symptoms across all diagnostic categories. Performance on explicit RL, but not implicit RL, was related to working memory, which accounted for some of the diagnostic group differences. However, working memory did not account for the relationship of explicit RL to motivation and pleasure symptoms. These findings suggest transdiagnostic relationships across the spectrum of psychotic disorders between motivation and pleasure impairments and explicit RL. (PsycINFO Database Record

Self versus informant reports on the specific levels of functioning scale: Relationships to depression and cognition in schizophrenia and schizoaffective disorder

The goal of the current study was to examine the relationships between insight and both cognitive function and depression in schizophrenia and schizoaffective disorder, and to determine if there were similar relationships across diagnostic categories. We examined discrepancies between self and informant reports of function on the Specific levels of function scale as a metric of insight for interpersonal, social acceptance, work and activities. We examined two samples of individuals with schizophrenia and/or schizoaffective disorder (Ns of 188 and 67 respectively). In Sample 1, cognition was measured using the Dot Probe Expectancy Task. In Sample 2, cognition was measured by averaging several subtests from the MATRICS consensus cognitive battery, as well as additional measures of working memory. In both samples, depression was measured using the Brief Psychiatric Rating Scale. In both samples, we found significant relationships between worse cognition and overestimations of work function, as well as between higher depression levels and underestimation of interpersonal function. These relationships were specific to interpersonal and work function, with significantly stronger correlations with interpersonal and work function compared to the other areas of function. Similar results were found across diagnostic categories. These results have important implications for treatment planning, as they suggest the need to take into account depression and cognitive function when evaluating the patient's self-report of function, and highlight the utility of informant reports in evaluating function and treatment planning. Further, they add to the literature on the similarity across schizophrenia and schizoaffective disorder in a variety of pathological mechanisms.

Functional network changes and cognitive control in schizophrenia

Cognitive control is a cognitive and neural mechanism that contributes to managing the complex demands of day-to-day life. Studies have suggested that functional impairments in cognitive control associated brain circuitry contribute to a broad range of higher cognitive deficits in schizophrenia. To examine this issue, we assessed functional connectivity networks in healthy adults and individuals with schizophrenia performing tasks from two distinct cognitive domains that varied in demands for cognitive control, the RiSE episodic memory task and DPX goal maintenance task. We characterized general and cognitive control-specific effects of schizophrenia on functional connectivity within an expanded frontal parietal network (FPN) and quantified network topology properties using graph analysis. Using the network based statistic (NBS), we observed greater network functional connectivity in cognitive control demanding conditions during both tasks in both groups in the FPN, and demonstrated cognitive control FPN specificity against a task independent auditory network. NBS analyses also revealed widespread connectivity deficits in schizophrenia patients across all tasks. Furthermore, quantitative changes in network topology associated with diagnostic status and task demand were observed. The present findings, in an analysis that was limited to correct trials only, ensuring that subjects are on task, provide critical insights into network connections crucial for cognitive control and the manner in which brain networks reorganize to support such control. Impairments in this mechanism are present in schizophrenia and these results highlight how cognitive control deficits contribute to the pathophysiology of this illness.

Impaired Context Processing is Attributable to Global Neuropsychological Impairment in Schizophrenia and Psychotic Bipolar Disorder

BACKGROUND

Context processing may reflect a specific cognitive impairment in schizophrenia. Whether impaired context processing is observed across psychotic disorders or among relatives of affected individuals, and whether it is a deficit that is independent from the generalized neuropsychological deficits seen in psychotic disorders, are less established.

METHODS

Schizophrenia, schizoaffective, and psychotic bipolar probands (n = 660), their first-degree relatives (n = 741), and healthy individuals (n = 308) studied by the Bipolar-Schizophrenia Network on Intermediate Phenotypes consortium performed an expectancy task requiring use of contextual information to overcome a pre-potent response. Sensitivity for target detection and false alarm rates on trials requiring inhibition or goal maintenance were measured.

RESULTS

Proband groups and relatives with psychosis spectrum personality traits demonstrated reduced target sensitivity and elevated false alarm rates. False alarm rate was higher under inhibition vs goal maintenance conditions although this difference was attenuated in schizophrenia and schizoaffective proband groups. After accounting for global neuropsychological impairment, as reflected by the composite score from the Brief Assessment of Cognition in Schizophrenia neuropsychological battery, deficits in schizophrenia and bipolar proband groups were no longer significant. Performance measures were moderately familial.

CONCLUSION

Reduced target detection, but not a specific deficit in context processing, is observed across psychotic disorders. Impairments in both goal maintenance and response inhibition appear to contribute comparably to deficits in schizophrenia and schizoaffective disorder, whereas greater difficulty with response inhibition underlies deficits in bipolar disorder. Yet, these deficits are not independent from the generalized neurocognitive impairment observed in schizophrenia and psychotic bipolar disorder.

The neural circuitry supporting goal maintenance during cognitive control: a comparison of expectancy AX-CPT and dot probe expectancy paradigms

Goal maintenance is an aspect of cognitive control that has been identified as critical for understanding psychopathology according to criteria of the NIMH-sponsored CNTRICS (Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia) and Research Domain Criteria (RDoC) initiatives. CNTRICS proposed the expectancy AX-CPT, and its visual-spatial parallel the dot probe expectancy (DPX), as valid measures of the cognitive and neural processes thought to be relevant for goal maintenance. The goal of this study was to specifically examine the functional neural correlates and connectivity patterns of both goal maintenance tasks in the same subset of subjects to further validate their neural construct validity and clarify our understanding of the nature and function of the neural circuitry engaged by the tasks. Twenty-six healthy control subjects performed both the letter (AX) and dot pattern (DPX) variants of the CPT during fMRI. Behavioral performance was similar between tasks. The 2 tasks engaged the same brain networks including dorsolateral prefrontal cortex (DLPFC) and dorsal parietal regions, supporting their validity as complementary measures of the goal maintenance construct. Interestingly there was greater engagement of the frontal opercular insula region during the expectancy AX-CPT (letter) and greater functional connectivity between the PFC and medial temporal lobe in the DPX (dot pattern). These differences are consistent with differential recruitment of phonological and visual-spatial processes by the two tasks and suggest that additional long-term memory systems may be engaged by the dot probe version.